This paper concerns optimal investment and consumption with CRRA utility when there is event risk. Events are modeled by transitions in a finite state Markov chain, but unlike traditional regime switching models, transitions not only change the instantaneous return statistics but are accompanied by jumps in the price at the instant of transition. Optimal investment and consumption policies are characterized using stochastic control methods and computed by solving a system of ordinary differential equations and a convex optimization problem. We show that optimal policies are significantly different from those of traditional regime switching or jump-diffusion problems and that the cost of ignoring transition price shocks can be substantial.

We study after-hours trading (AHT), price contributions, and price discovery following quarterly earnings announcements released outside of the normal trading hours. For Standard & Poor’s (S&P) 500 index stocks from 2004–2008, AHT is heightened on announcement days. A significant portion of the price change and price discovery occurs immediately after the earnings releases. Prices in AHT show a large degree of informational efficiency, further demonstrating the importance of price discovery in AHT. We also provide evidence suggesting that firms prefer after-hours earnings announcements, as trades are mainly from informed traders, and those trades are relied upon to convey information to the general public.

As the role of virtual teams in organizations becomes increasingly important, it is crucial that companies identify and leverage team members’ knowledge. Yet, little is known of how virtual team members come to recognize one another’s knowledge, trust one another’s expertise, and coordinate their knowledge effectively. In this study, we develop a model of how three behavioral dimensions associated with transactive memory systems (TMS) in virtual teams expertise location, task knowledge coordination, and cognition-based trust and their impacts on team performance change over time. Drawing on the data from a study that involves 38 virtual teams of MBA students performing a complex web-based business simulation game over an 8-week period, we found that in the early stage of the project, the frequency and volume of task-oriented communications among team members played an important role in forming expertise location and cognition-based trust. Once TMS were established, however, task-oriented communication became less important. Instead, toward the end of the project, task knowledge coordination emerges as a key construct that influences team performance, mediating the impact of all other constructs. Our study demonstrates that TMS can be formed even in virtual team environments where interactions take place solely through electronic media, although they take a relatively long time to develop. Furthermore, our findings show that, once developed, TMS become essential to performing tasks effectively in virtual teams.

Research on the diffusion of management accounting innovations (MAIs) has grown into a substantial literature which draws attention to how diffusion processes can be fuelled by compulsory regulation. However, relatively little is known about how MAIs interact with wider regulatory processes in society and how this affects the adaptation of such innovations as they diffuse across organisations. This paper extends research on this topic by addressing the questions of how regulators mediate the adaptation of MAIs and how this mediation affects the use of such innovations across regulatees. We explore these questions in relation to the evolution of Economic Value Added (EVA™) as a compulsory performance management system for state-owned enterprises (SOEs) in Thailand. Theoretically, we extend research on management innovations with sociological research, which sees regulation as an evolving and collaborative process that unfolds as an integral part of broader, societal reform programmes. Consistent with this perspective, we show how regulators can fill a key role as mediators by engaging in ongoing consultations with the suppliers of MAIs as well as regulatees, and how this imbues the regulatory standards that govern the use of such innovations with considerable flexibility. We also extend this perspective on regulation by showing how the regulatory standards governing EVA™ were influenced by multiple, and partly competing, reform programmes centred on other innovations. In addition, we show how the mediating role of regulators enables regulatees to influence the evolution of regulatory standards and how this facilitates compliance with regulation and allows regulatees to adapt MAIs to industry-specific regulations and cultural characteristics. We discuss the implications of these findings for the sociological literature on regulation informing this paper and for research on the diffusion of MAIs.

Increasingly, public sector organisations are being encouraged or required to provide service performance information in addition to financial statements. Yet, reporting is often inferior, as shown by this example of local governments in New Zealand. Poor quality reporting has led to different initiatives to improve service performance reporting quality, and this study investigates the effectiveness of three initiatives undertaken by the Auditor-General. Drawing on contemporary institutional and legitimacy theories, we find that normative pressure in tandem with threats to legitimacy is influential in improving service performance reporting. However, despite mimetic examples also being used, the analysis shows it is an ineffective tool in the New Zealand local government context.

Purpose – The purpose of this paper is to explore the adoption of a mobile insurance claim system (M-insurance) and develops a framework for the adoption of M-insurance by consumers. Design/methodology/approach – This study assesses mobile technology for claim management through the lens of the technology acceptance model (TAM) and diffusion of innovation (DOI) models as a major guideline, using exploratory research through in-depth interviews with four executive experts who are first movers in mobile claim motor insurance in Thailand. Semi-structured interviews and open-ended questions were used to conduct group interviews of insurance consumers who mostly use smartphones. The data were collected in a qualitative research approach from Thai insurance consumers (n=177), and contents were classified and analysed to gain strong insights into respondent opinions, comments, attitudes, behaviour, and experiences. Findings – The results indicate that the external (social) factors influence attitude and behaviour of consumers which link to their intention to adopt M-insurance. These external factors include: preference for face-to-face service; confidence of insurers in accepting claim; and risk of claim knowledge that might cause legal issues among others. In application, the findings shall meaningfully enhance insurer firms’ improvement of adoption rate and development of future features and functions of M-insurance. Research limitations/implications – This study is based on insurance consumers in each region of Thailand but focuses only on mobile claim management for motor insurance. Although the findings bring new insight and understanding of consumer preferences and behaviours, they were not tested statistically. Practical implications – The study has practical implications for motor insurance claimants who are concerned over the complicated policy conditions, the perspective risk of claim knowledge and fault admission, and the on-site investigation by surveyor for another party. These are the guidance impediments to overcome M-insurance adoption improvement. Originality/value – Previously, TAM and DOI approaches have been employed to study general adoption of M-banking by quantitative research which confirmed descriptive data and tested the hypothesis, but neglected crucial data. However, M-insurance is different from M-banking in term of features and functions, purpose and process of usage, and legal liability. Therefore, this study is one of a few empirical studies that attempt to identify insightful factors to consumer uptake of M-insurance which is in its early stage and lacks an underpinning TAM model. This study contributes by identifying insights of “pull” factors to successfully develop M-insurance in Thailand.

Abstract

Prevailing wisdom on “pay what you want” (PWYW) pricing focuses on the influence of altruism or fairness on consumers’ payments. In this paper, we offer a different perspective by demonstrating that, if the seller and consumers interact repeatedly, and future provision of PWYW depends on whether current revenue under PWYW is sufficient for the seller to achieve financial goals, then paying under PWYW can be likened to paying for a threshold public good. Our model implies that continuous provision of PWYW can be profitable even when all consumers are self-interested. We find in two experiments that if there is pre-payment online chat-room-style communication among consumers, then efficient tacit coordination at the payment stage can be accomplished to achieve continuous PWYW provision. We also show experimentally that pre-payment communication can sustain PWYW provision even when consumers have limited feedback about each other’s payments, or limited information about the market.

The marginal benefits of diversification exceed the costs by a decreasing margin, and diversifying beyond the optimal level will produce a wealth loss. This trade-off predicts an inverted U-relation between the degree of diversification and wealth. We find empirical evidence in support of this trade-off proposition. Consistent with the trade-off, firms diversify cautiously and stop diversifying before the marginal benefits are offset by the costs. Our findings lend support to the arguments suggesting efficient diversification. In line with the endogeneity of diversification, the findings also indicate that the optimal level of diversification can vary across firms depending on their reasons for diversifying.
Diversification gains follow an inverted U-relation between degree of diversification and wealth. Firms diversify cautiously and stop diversifying before benefits are offset by costs. Results are consistent with arguments indicating efficient diversification. Optimal level of diversification can vary across firms depending on reasons for diversifying.

The focus of this article is on failure history of a repairable system for which the relevant data comprise successive event times for a recurrent phenomenon along with an event-count indicator. We undertake an investigation for analyzing failures from repairable systems that are subject to multiple failure modes. Failure data representing a cluster of recurrent events from a single system are studied under the parametric framework of apower-law process, a model that has found considerable attention in industrial applications. Some interesting and nonstandard asymptotic results ensue in this context that are discussed in detail. Extensive simulation has been carried out that supplements the theoretical findings. An extension to the case where the specific cause of failure may be missing is investigated in detail. The methodology has been implemented on recurrent failure data obtained from a warranty claim database for a fleet of automobiles. Supplementary material for this article is available online.

The relevance in society of management accounting innovations as seen from the economic value added and institutional work in the fields of Chinese and Thai state-owned enterprises is discussed. The way in which different types of institutional works support and detract from each other is also highlighted.

This paper undertakes an out-of-sample test of developed-country insider trading regulation in an emerging market environment (Thailand), where severe information asymmetry, lax enforcement and poor pricing efficiency are endemic. Thai insider trading regulation, which mimics developed market rules, fails on all three measures of success. Insiders trade with impunity during a regulated trading ban. Their trading performance outperforms other investors at all times, and they continue to exploit their privileged position with respect to information flow. Our study suggests it is inappropriate for emerging market regulators to adopt developed market regulation without first considering the unique characteristics of their own environment.

Underpricing of IPOs in Thailand significantly drops following the country’s major governance reform, indicating less price-protection by investors. The lower price-protection is associated with fewer instances of absolute control retention by pre-issue insiders during the post-reform period, not reduction in the expropriation risk. While corporate disclosure does not reveal issuers’ true risk type before the reform, it does so after the reform. Yet, insiders make significantly less disclosure when retaining absolute control regardless of the reform. We conclude that governance regulation in an economy with fundamentally weak legal institutions works, but its efficacy is limited when insiders retain absolute control.

We examine the relation between the quality of corporate governance practices and firm value for Thai firms, which often have complex ownership structures. We develop a comprehensive measure of corporate governance and show that, in contrast to conventional measures of corporate governance, our measurement, on average, is positively associated with Tobin’s q. Furthermore, we find that q values are lower for firms that exhibit deviations between cash flow rights and voting rights. We also find that the value benefits of complying with “good” corporate governance practices are nullified in the presence of pyramidal ownership structures, raising doubts on the effectiveness of governance measures when ownership structures are not transparent. We conclude that family control of firms through pyramidal ownership structures can allow firms to seemingly comply with preferred governance practices but also use the control to their advantage.

We formulate a mean-variance portfolio selection problem that accommodates qualitative input about expected returns and provide an algorithm that solves the problem. This model and algorithm can be used, for example, when a portfolio manager determines that one industry will benefit more from a regulatory change than another but is unable to quantify the degree of difference. Qualitative views are expressed in terms of linear inequalities among expected returns. Our formulation builds on the Black-Litterman model for portfolio selection. The algorithm makes use of an adaptation of the hit-and-run method for Markov chain Monte Carlo simulation. We also present computational results that illustrate advantages of our approach over alternative heuristic methods for incorporating qualitative input. Keywords: portfolio selection, Bayesian inference

This study uses time-series data to examine the relation between changes in the quality of corporate governance practices and subsequent market valuation among large listed companies in Hong Kong. The results indicate that firms that exhibit improvements in the quality of corporate governance display a subsequent increase in market valuation, whereas firms that exhibit deterioration in the quality of corporate governance practices tend to encounter a decline in market valuation. Additionally, the impact is greater for firms that are included in the MSCI index or with a China affiliation. The results provide evidence in support of the notion that good corporate governance can predict future market valuation.

In this paper, we introduce a new approach for finding robust portfolios when there is model uncertainty. It differs from the usual worst-case approach in that a (dynamic) portfolio is evaluated not only by its performance when there is an adversarial opponent (‘nature’), but also by its performance relative to a stochastic benchmark. The benchmark corresponds to the wealth of a fictitious benchmark investor who invests optimally given knowledge of the model chosen by nature, so in this regard, our objective has the flavor of min-max regret. This relative performance approach has several important properties: (i) optimal portfolios seek to perform well over the entire range of models and not just the worst case, and hence are less pessimistic than those obtained from the usual worst-case approach; (ii) the dynamic problem reduces to a convex static optimization problem under reasonable choices of the benchmark portfolio for important classes of models including ambiguous jump-diffusions; and (iii) this static problem is dual to a Bayesian version of a single period asset allocation problem where the prior on the unknown parameters (for the dual problem) correspond to the Lagrange multipliers in this duality relationship. This dual static problem can be interpreted as a less pessimistic alternative to the single period worst-case Markowitz problem. More generally, this duality suggests that learning and robustness are closely related when benchmarked objectives are used.

We consider the problem of sampling a point from an arbitrary distribution π over an arbitrary subset S of an integer hyperrectangle. Neither the distribution π nor the support set S are assumed to be available as explicit mathematical equations, but may only be defined through oracles and, in particular, computer programs. This problem commonly occurs in black-box discrete optimization as well as counting and estimation problems. The generality of this setting and high dimensionality of S precludes the application of conventional random variable generation methods. As a result, we turn to Markov chain Monte Carlo (MCMC) sampling, where we execute an ergodic Markov chain that converges to π so that the distribution of the point delivered after sufficiently many steps can be made arbitrarily close to w. Unfortunately, classical Markov chains, such as the nearest-neighbor random walk or the coordinate direction random walk, fail to converge to π because they can get trapped in isolated regions of the support set. To surmount this difficulty, we propose discrete hit-and-run (DHR), a Markov chain motivated by the hit-and-run algorithm known to be the most efficient method for sampling from log-concave distributions over convex bodies in Rn. We prove that the limiting distribution of DHR is Tπ as desired, thus enabling us to sample approximately from Tπ by delivering the last iterate of a sufficiently large number of iterations of DHR. In addition to this asymptotic analysis, we investigate finite-time behavior of DHR and present a variety of examples where DHR exhibits polynomial performance.

Relaxed disclosure requirements of unlisted firms, as compared to publicly listed companies, lead to limited quality and quantity of information at bid announcements, causing difficulty in valuing gains from mergers. This raises the question: are the frequently reported superior announcement-period gains to unlisted-target acquirers sustainable in the long run? Our results for the UK show that unlisted-target acquirers gain on announcement, but suffer a substantial loss in the long run. This reversal in fortune of unlisted-target acquirers is in sharp contrast to the performance of listed-target acquirers in the UK. Therefore, short-run gains for unlisted-target acquirers may result from investors’ excessive optimism when faced with limited and biased information.

This paper develops numerical approximations for pricing collateralized debt obligations (CDOs) and other portfolio credit derivatives in the multifactor Normal Copula model. A key aspect of pricing portfolio credit derivatives is capturing dependence between the defaults of the elements of the portfolio. But, compared with an independent-obligor model, pricing in a model with correlated defaults is more challenging. Our approach strikes a balance by reducing the problem of pricing in a model with correlated defaults to calculations involving only independent defaults. We develop approximations based on power series expansions in a parameter that scales the underlying correlations. These expansions express a CDO tranche price in a multifactor model as a series of prices in independent-obligor models, which are easy to compute. The approach builds on a classical approximation for multivariate Gaussian probabilities; we introduce an alternative representation that greatly reduces the number of terms required to evaluate the coefficients in the expansion. We also apply this method to the underlying problem of computing joint probabilities of multivariate normal random variables for which the correlation matrix has a factor structure.

Many studies have observed that close interfirm collaborations have positive effects on a firm’s innovation. Yet, they have not shown how the collaboration contributes to this process. Higher innovation rates could be a result of revolutionary improvements, evolutionary improvements, or both. We investigated changes in the innovation process. Longitudinal data from 23 top IT firms across 9 years were collected and analyzed. Results suggested that close interfirm collaborations were associated with evolutionary but not revolutionary improvement. Results also suggested that the longer the IT firms had engaged in close interfirm collaboration, the larger the effect on IT innovations.

The authors study the properties of graphical estimators with multiply right-censored data and compare their performance with that of maximum likelihood estimators. The study yielded large-sample results on consistency, asymptotic normality, and asymptotic variance expressions. Small-sample properties are studied for selected distributions and censoring patterns. The results extend the work of Nair (1984) to right-censored data.

Harris, R. D. F., & Pisedtasalasai, A. (2006). Return and Volatility Spillovers between Large and Small Stocks in the UK. Journal of Business Finance and Accounting, 33(9-10), 1556-1571.

Abstract

This paper investigates return and volatility spillover effects between the FTSE 100, FTSE 250 and FTSE Small Cap equity indices using the multivariate GARCH framework. We find that return and volatility transmission mechanisms between large and small stocks in the UK are asymmetric. In particular, there are significant spillover effects in both returns and volatility from the portfolios of larger stocks to the portfolios of smaller stocks. For volatility, there is also evidence of limited feedback from the portfolios of smaller stocks to the portfolios of larger stocks, although sub-period analysis suggests that this is to some extent period-specific. Simulation evidence shows that non-synchronous trading potentially explains some, but not all, of the spillover effects in returns, and that it explains none of the spillover effects in volatility. These results are consistent with a market in which information is first incorporated into the prices of large stocks before being impounded into the prices of small stocks.

A thermoelectric generator’s battery charging performance using an application of step-up direct current (DC)–DC converter to harvest energy was researched. In the first-stage study, temperature gradients from different potential heat or cold sources around individuals’ daily lives were harnessed as power supplies for personal electronic gadgets. A primary prototype comprised four components including four bulk thermoelectric modules (with 127 thermoelectric-element couples per module). Its charging characteristics was evaluated under five conditions of use. It produced the maximum power of 4.82 W, and utilized the lowest starting temperature difference of 26°C. Thermoelectric-conversion charging using a constant-heat electric stove yielded charging characteristics comparisons among three prototypes and two commercial products in the second-stage study. Despite approximately 40% less Seebeck coefficient under the same experimental conditions, the prototype indicated competitive characteristics in battery charging comparison with higher output power and more charging efficiency in the first 45 min of charging of the lower temperature-difference condition. All prototypes, with competitive maximum unit cost of US$110, yielded maximum thermal-to-electric charging efficiency and boosted the converter’s efficiency in the range of 3.8–4.8% and 60–78%, respectively.

This paper considers the problem of comparing two processes or treatments which are each modelled with a Weibull distribution. Win-probabilities are considered, which compare potential single future observations from each of the two treatments. This information can be useful in helping decide which of the two treatments to adopt, and can be combined with other factors relevant to a practitioner such as the availabilities, costs and side-effects of the two treatments. A methodology employing joint confidence sets is developed which not only allows estimation and confidence interval construction for the win-probabilities, but at the same guaranteed confidence level also tests whether Weibull distributions are appropriate for the data, identifies any common Weibull distributions for the two processes and also provides individual inferences for the two Weibull distributions. Examples are given to illustrate the implementation and application of this methodology, for which R computer code is available from the authors. This methodology can be extended to different models such as other two-parameter and three-parameter Weibull models, and to the comparison of three or more Weibull distributions.

This article considers the problem of choosing between two treatments that have binary outcomes with unknown success probabilities p1 and p2. The choice is based upon the information provided by two observations X1 ∼ B(n1, p1) and X2 ∼ B(n2, p2) from independent binomial distributions. Standard approaches to this problem utilize basic statistical inference methodologies such as hypothesis tests and confidence intervals for the difference p1 − p2 of the success probabilities. However, in this article the analysis of win-probabilities is considered. If X*1 represents a potential future observation from Treatment 1 while X*2represents a potential future observation from Treatment 2, win-probabilities are defined in terms of the comparisons of X*1 and X*2. These win-probabilities provide a direct assessment of the relative advantages and disadvantages of choosing either treatment for one future application, and their interpretation can be combined with other factors such as costs, side-effects, and the availabilities of the two treatments. In this article, it is shown how confidence intervals for the win-probabilities can be constructed, and examples of their use are provided. Computer code for the implementation of this new methodology is available from the authors.

Consider a set of independent random variables with specified distributions or a set of multivariate normal random variables with a product correlation structure. This paper shows how the distributions and moments of these random variables can be calculated conditional on a specified ranking of their values. This can be useful when the ordering of the variables can be determined without observing the actual values of the variables, as in ranked set sampling, for example. Thus, prior information on the distributions and moments from their individual specified distributions can be updated to provide improved posterior information using the known ranking. While these calculations ostensibly involve high dimensional integral expressions, it is shown how the previously developed general recursive integration methodology can be applied to this problem so that they can be evaluated in a straightforward manner as a series of one-dimensional or two-dimensional integral calculations. Furthermore, the proposed methodology possesses a self-correction mechanism in the computation that prevents any serious growth of the errors. Examples illustrate how different kinds of ranking information affect the distributions, expectations, variances, and covariances of the variables, and how they can be employed to solve a decision making problem.

Conference calls have become a widely used medium for voluntary corporate disclosure, especially among firms associated with greater information asymmetry, intangible assets, and external competition. These features are common in high-tech sectors, which dominate the Taiwanese economy and render it a useful research setting for investigating whether board interlock, as a social network, affects corporate decisions to hold conference calls. We show that firms connected to conference-call-making firms through interlocked directors are more likely to hold conference calls and the frequency of holding conference calls increases with interlocking directors’ relevant experience. Moreover, such evidence is more pronounced if the connections are held through independent directors and among firms with greater information asymmetry. These results support the argument that the spread of corporate practices is positively associated with board interlock networks. Our findings have implications for the choice of board of director members, and can be generalized to other emerging economies characterized by weaker corporate information environments.

This is an exploratory study to examine the quality or usefulness of accounting estimates of companies in China and India over time. Specifically, we examine how well the accounting estimates are able to predict future earnings and cash flows during the period 2003-2013. The results for India indicate that the out-of-sample earnings and cash flow predictions derived are more accurate and more efficient in the more recent period (2010-2013) than the earlier period (2003-2006). In contrast, the out-of-sample earnings and cash flow predictions for China are generally more biased, less accurate, and less efficient. The results indicate abnormal returns earned on hedge portfolios formed on earnings (cash flow) predictions for India in the recent period. In contrast, none of the portfolios for China earn positive returns. The results suggest that the accounting estimates in India in recent years have become better predictors of future earnings and cash flow than accounting estimates in the earlier period. However, the accounting estimates in China are not relevant for predicting earnings and cash flows over the years in the sample period.

Tax incentives are one of the most important fiscal tools at the government’s disposal that can be used to influence the economy. Often, policies are targeted to spur investment in durable goods. In this article, we focus on the impact that a primary-market tax incentive has on the secondary market for durable goods – specifically, the automobile market. Using a first-car tax rebate scheme implemented in Thailand in 2011 as a natural experiment, we find that the policy reduces the listing prices of used cars in the tax-eligible category by 6.75% to 10.31%.

The objectives of this study were to reduce the amounts of biogenic amines (BAs) and cholesterol in Thai fermented pork sausage (Nham) using the γ-aminobutyric acid (GABA) producers, Pediococcus pentosaceus HN8 and Lactobacillus namurensis NH2, as a mixed starter (6 log CFU/g for each strain). The distribution of lactic acid bacteria (LAB) was also monitored to follow the prevalence of the mixed starter during fermentations. The starter cultures in the inoculated Nham sets (TSM, starter + 5 g/kg monosodium glutamate, MSG; and TSN, starter + no MSG) reduced the amounts of 7 BAs to meet the safety regulation requirements in the order of β-phenylethylamine > histamine > tyramine > putrescine > spermine > spermidine > cadaverine. In contrast, with the control fermentations (TNN, no starter + no MSG and TNM, no starter + MSG, 5 g/kg) only histamine was higher than the recommended level. Cholesterol content was also reduced by 35% in the GABA Nham set (TSM, GABA 3962 mg/kg) when compared with the TNN; and this was significantly lower than the popular commercial Nham brands (114–125 mg cholesterol/100 g). Determination of the LAB succession confirmed that the starter cultures played the biggest roles in reducing both the BAs and cholesterol levels.
A mixed probiotic of Lactobacillus namurensis NH2 and Pediococcus pentosaceus HN8 was dominant in Nham. Inoculated Nham reduced 7 biogenic amines to meet the safety regulation requirements. Inoculated Nham with monosodium glutamate, 5 g/kg had 3962 mg/kg γ-aminobutyric acid. Cholesterol content in GABA Nham was much lower than that in commercial Nham brands. A novel fermented pork sausage (Nham) that is safe and healthier has been developed.

Using a unique, multi-year sample of publicly traded non-financial companies in Thailand, I find the level of family ownership influences the level of investment. The results are from an emerging market, which features concentrated, family-dominated corporate ownership structures, including ownership pyramids. Firms with higher levels of family ownership show higher investment ratios, whether the ratio is a fixed assets-based measure or a cash flow-based measure. The investment ratios exhibit greater sensitivity to financial slack. However, these two relations are dependent on the level of family ownership. I find evidence of underinvestment at lower levels of family ownership, plus evidence of overinvestment at family firms which employ pyramidal ownership structures. The results have implications for the efficiency of investment at family-owned firms.

This paper aims to develop a new economic assessment (EA) method using the option to expand for Advanced Process Control (APC) and Real Time Optimization (RTO). The new EA criteria for investment decision for APC and RTO employ net present value of APC and call option of RTO. Calculation of call option adapts arithmetic measurement method to compute annualized volatility. The new EA applies scenario analysis to take appropriate action. There are four scenarios and their corresponding actions, namely, (1) safe scenario – invest only APC, (2) value-added scenario and (3) risky scenario – invest in APC and RTO, (4) gamble scenario – reject APC. Furthermore, early exercise criterion for RTO investment uses American option method. Applying new EA method to VCM plant demonstrates the effectiveness of the option to expand. The results show that when NPV of APC is negative and the sum of NPV of APC and Call of RTO is positive, APC project is risky scenario. We recommend to invest in APC and RTO. In comparison to conventional NPV and Payback Period (PB) methods, APC is not feasible since NPV is negative and PB is not available due to negative expected profit. In the case study, volatility calculation addresses only one product line in chemical industry which is VCM. Real production comprises of multiple product lines and their volatility is larger than that of one product. With the new EA method, management has comprehensive and flexible tool to assess APC/RTO benefits. Moreover, the new EA provides the timing to invest RTO. Profit margin, expiration period and yield are key parameters that affect early exercise. The new EA is the first method to apply real options to APC and RTO which evaluates the benefit not only APC but also the integrated APC and RTO. The early exercise criterion can facilitate the decision maker to invest in the most beneficial period.

One of the basic graphical methods for assessing the validity of a distributional assumption is the Q-Q plot which compares quantiles of a sample against the quantiles of the distribution. In this paper, we focus on how a Q-Q plot can be augmented by intervals for all the points so that, if the population distribution is Weibull or exponential then all the points should fall inside the corresponding intervals simultaneously with probability 1 − α. These simultaneous 1 − α probability intervals provide therefore an objective mean to judge whether the plotted points fall close to the straight line: the plotted points fall close to the straight line if and only if all the points fall within the corresponding intervals. The powers of five Q-Q plot based graphical tests and the most popular non-graphical Anderson-Darling and Cramér-von-Mises tests are compared by simulation. Based on this power study, the tests that have better powers are identified and recommendations are given on which graphical tests should be used in what circumstances. Examples are provided to illustrate the methods.

Infinite horizon optimization (IHO) problems present a number of challenges for their solution, most notably, the inclusion of an infinite data set. This hurdle is often circumvented by approximating its solution by solving increasingly longer finite horizon truncations of the original infinite horizon problem. In this paper, we adopt a novel transformation that reduces the infinite dimensional IHO problem into an equivalent one dimensional optimization problem, i.e., minimizing a Holder continuous objective function with known parameters over a closed and bounded interval of the real line. We exploit the characteristics of the transformed problem in one dimension and introduce an algorithm with a graphical implementation for solving the underlying infinite dimensional optimization problem.

The bidirectional shortest path problem has important applications in VLSI floor planning and other areas. We introduce a new algorithm to solve bidirectional shortest path problems using parallel architectures provided by general purpose computing on graphics processing units. The algorithm performs parallel searches from the source and sink using Dijkstra’s classic approach modified with pruning and early termination. We achieve substantial speedup over a parallel method that performs a single parallel search on the GPGPU from the source to all other nodes but early terminates when the shortest path to the specified target node is found. Experimental results demonstrate a speedup of nearly 2× over the parallel method that performs a parallel search from the source with early termination on the GPGPU.

In this study, we examine a setting in which overreliance on structured materiality guidance leads to less appropriate materiality assessments by auditors, and investigate whether a justification requirement in the absence of accountability mitigates this effect. Results from our experiment show that audit managers make less conservative and less appropriate planning materiality assessments in the presence of structured materiality guidance, but that this detrimental effect is mitigated by the need to justify their judgments. Our study on the joint effect of these two features extends current literature on materiality judgments and has implications for audit practice.